Article
Statistics & Probability
Tsung- Lin, Wan-Lun Wang
Summary: This paper derives explicit expressions for the moments of truncated multivariate normal/independent distributions with supports confined within a hyper-rectangle. A Monte Carlo experiment is conducted to validate the proposed formulae for five selected members of the distributions.
JOURNAL OF MULTIVARIATE ANALYSIS
(2024)
Article
Statistics & Probability
Omidali Aghababaei Jazi
Summary: In this paper, a pseudo-partial likelihood estimation method is proposed to estimate parameters in the Cox proportional hazards model with right-censored and biased sampling data by adjusting sample risk sets. The asymptotic properties of the resulting estimator are studied, and a simulation study is conducted to illustrate the finite sample performance. The proposed method is also applied to analyze a set of HIV/AIDS data.
JOURNAL OF STATISTICAL PLANNING AND INFERENCE
(2024)
Article
Statistics & Probability
Chuancun Yin, Narayanaswamy Balakrishnan
Summary: The family of multivariate skew-normal distributions has interesting properties, which also hold for a general class of skew-elliptical distributions.
JOURNAL OF MULTIVARIATE ANALYSIS
(2024)
Article
Statistics & Probability
Clement Foucart, Matija Vidmar
Summary: This study introduces a class of one-dimensional positive Markov processes that generalize continuous-state branching processes by incorporating random collisions. The study establishes that these processes, known as CB processes with collisions (CBCs), are the only Feller processes without negative jumps that satisfy a Laplace duality relationship with one-dimensional diffusions. The study also explores the relationship between CBCs and CB processes with spectrally positive migration, and provides necessary and sufficient conditions for attracting boundaries and the existence of a limiting distribution.
STOCHASTIC PROCESSES AND THEIR APPLICATIONS
(2024)
Article
Statistics & Probability
Renan Gross
Summary: This study focuses on the problem of scenery reconstruction on d-dimensional torus. The researchers proved that the criterion on Fourier coefficients for discrete cycles, discovered by Matzinger and Lember in 2006, also applies in continuous spaces. It is shown that with the right drift, Brownian motion can be used to reconstruct any scenery. The injectivity property of an infinite Vandermonde matrix is also proven.
STOCHASTIC PROCESSES AND THEIR APPLICATIONS
(2024)
Article
Computer Science, Interdisciplinary Applications
Jie Liu, Zifeng Ye, Kun Chen, Panpan Zhang
Summary: This paper introduces a network-based method for collaborative filtering in recommender systems. The proposed method, a novel mixed-membership stochastic block model with a conjugate prior, is derived and a computationally feasible variational Bayesian algorithm is presented. Extensive simulations show that the proposed model provides more accurate inference compared to competing methods, even with the presence of outliers. The model is also applied to a real MovieLens dataset for validation.
COMPUTATIONAL STATISTICS & DATA ANALYSIS
(2024)
Article
Statistics & Probability
Wanfeng Liang, Xiaoyan Ma
Summary: This paper proposes a method for estimating ultrahigh dimensional covariance matrix without assuming Gaussian distribution and the order of variables. By combining modified Cholesky decomposition and refitted cross validation, the proposed method, CovPRCV, is able to attenuate spurious correlation in the ultrahigh dimensional data under the Permutation-Average framework. The consistency of the proposed estimator is derived under the Frobenius norm without the need for banded structure and normal distribution. Simulation studies demonstrate the promising performance of the proposed method compared to its competitors in various scenarios. The method is also applied to analyze a prostate dataset.
STATISTICS & PROBABILITY LETTERS
(2024)
Article
Statistics & Probability
Aurore Lavigne, Silvia Liverani
Summary: Bayesian clustering models face challenges in analyzing the uncertainty of data partitions. This paper proposes a numerical and graphical method to quantify the uncertainty of clusterings and suggests how this tool can be used to learn about partition uncertainty.
STATISTICS & PROBABILITY LETTERS
(2024)
Article
Computer Science, Interdisciplinary Applications
L. M. Andre, J. L. Wadsworth, A. O'Hagan
Summary: This paper proposes a dependence model that captures the entire data range in multi-variable cases. By blending two copulas with different characteristics and using a dynamic weighting function for smooth transition, the model is able to flexibly capture various dependence structures.
COMPUTATIONAL STATISTICS & DATA ANALYSIS
(2024)
Article
Computer Science, Interdisciplinary Applications
Niwen Zhou, Xu Guo, Lixing Zhu
Summary: The paper investigates hypothesis testing regarding the potential additional contributions of other covariates to the structural function, given the known covariates. The proposed distance-based test, based on Neyman's orthogonality condition, effectively detects local alternatives and is robust to the influence of nuisance functions. Numerical studies and real data analysis demonstrate the importance of this test in exploring covariates associated with AIDS treatment effects.
COMPUTATIONAL STATISTICS & DATA ANALYSIS
(2024)
Article
Statistics & Probability
Abid Hussain, Steve Drekic, Salman A. Cheema
Summary: This research introduces a new ranking scheme that can order competing units in a more continuous manner. The proposed formula incorporates data range and quantile coverage to enhance the sensitivity of the weights of competing observations. The proposed approach has the ability to offer unambiguous preferences.
STATISTICS & PROBABILITY LETTERS
(2024)
Article
Statistics & Probability
Gaspard Bernard, Thomas Verdebout
Summary: In this paper, we address the problem of testing the relationship between the eigenvalues of a scatter matrix in an elliptical distribution. Using the Le Cam asymptotic theory, we show that the non-specification of nuisance parameters has an asymptotic cost for testing the relationship. We also propose a distribution-free signed-rank test for this problem.
JOURNAL OF MULTIVARIATE ANALYSIS
(2024)
Article
Computer Science, Interdisciplinary Applications
Rebeca Pelaez, Ingrid Van Keilegom, Ricardo Cao, Juan M. Vilar
Summary: This article proposes an estimator for the probability of default (PD) in credit risk, derived from a nonparametric conditional survival function estimator based on cure models. The asymptotic expressions for bias, variance, and normality of the estimator are presented. Through simulation and empirical studies, the performance and practical behavior of the nonparametric estimator are compared with other methods.
COMPUTATIONAL STATISTICS & DATA ANALYSIS
(2024)
Article
Statistics & Probability
Nader Karimi, Erfan Salavati, Hirbod Assa, Hojatollah Adibi
Summary: This paper proposes a continuous time version of the speculative storage model for commodity prices and provides mathematical analysis and numerical algorithm verification for the model.
STATISTICS & PROBABILITY LETTERS
(2024)
Article
Statistics & Probability
Marlene Baumeister, Marc Ditzhaus, Markus Pauly
Summary: This paper introduces a more robust multivariate analysis method by using general quantiles, particularly the median, instead of the traditional mean, and applies and validates this method on various factorial designs. The effectiveness of this method is demonstrated through theoretical and simulation studies on small and moderate sample sizes.
JOURNAL OF MULTIVARIATE ANALYSIS
(2024)
Article
Economics
Anna Rita Bacinello, Rosario Maggistro, Ivan Zoccolan
Summary: In this paper, a model is proposed for pricing GLWB variable annuities under a stochastic mortality framework. The contract value is defined through an optimization problem solved by using dynamic programming. The authors prove the validity of the bang-bang condition for the withdrawal strategies of the model using backward induction. Extensive numerical examples are presented, comparing the results for different parameters and policyholder behaviours.
INSURANCE MATHEMATICS & ECONOMICS
(2024)
Article
Engineering, Mechanical
Jiaqi Wang, Zhenzhou Lu, Lu Wang
Summary: This paper proposes an efficient method to estimate the FP-GS using reliability updating, avoiding the time-consuming double-loop structure analysis. By utilizing the likelihood function and adaptive Kriging model, the unconditional FP and all conditional FPs can be estimated simultaneously.
PROBABILISTIC ENGINEERING MECHANICS
(2024)
Article
Engineering, Mechanical
Lujie Shi, Leila Khalij, Christophe Gautrelet, Chen Shi, Denis Benasciutti
Summary: This study proposes an innovative Two-phase method based on the Langlie method and the D-optimality criterion to overcome the intrinsic shortcomings of the staircase method used in estimating the fatigue limit distribution. Through simulation-based study, it is demonstrated that the proposed method improves the estimation performance for the mean and standard deviation of the fatigue limit distribution.
PROBABILISTIC ENGINEERING MECHANICS
(2024)
Article
Statistics & Probability
M. Heldman, S. A. Isaacson, J. Ma, K. Spiliopoulos
Summary: This study derives and proves the large-population mean-field limit for particle-based stochastic reaction-diffusion models, and provides the next order fluctuation corrections. Numerical examples demonstrate the importance of fluctuation corrections for accurate estimation of higher order statistics in the underlying model.
STOCHASTIC PROCESSES AND THEIR APPLICATIONS
(2024)
Article
Statistics & Probability
Antonio Di Noia, Gianluca Mastrantonio, Giovanna Jona Lasinio
Summary: Building on Dryden et al. (2021), this note presents the Bayesian estimation of a regression model for size-and-shape response variables with Gaussian landmarks, fitting into the framework of Bayesian latent variable models and potentially allowing for a highly flexible modeling framework.
STATISTICS & PROBABILITY LETTERS
(2024)
